ArticleMedical care2018
The Impact of Nondifferential Exposure Misclassification on the Performance of Propensity Scores for Continuous and Binary Outcomes: A Simulation Study.
Article in Medical care, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Groundwater quality and hypertension in India: addressing misclassification and predictive accuracy in Biswas et al.Journal of exposure science & environmental epidemiology · 2026Article
- Article
- Groundwater Chemistry and Blood Pressure: A Cross-Sectional Study in Bangladesh.International journal of environmental research and public health · 2019Article
- Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control.Pharmacoepidemiology and drug safety · 2018Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
purposeTo investigate the ability of the propensity score (PS) to reduce confounding bias in the presence of nondifferential misclassification of treatment, using simulations.
methodsUsing an example from the pregnancy medication safety literature, we carried out simulations to quantify the effect of nondifferential misclassification of treatment under varying scenarios of sensitivity and specificity, exposure prevalence (10%, 50%), outcome type (continuous and binary), true outcome (null and increased risk), confounding direction, and different PS applications (matching, stratification, weighting, regression), and obtained measures of bias and 95% confidence interval coverage.
resultsAll methods were subject to substantial bias toward the null due to nondifferential exposure misclassification (range: 0%-47% for 50% exposure prevalence and 0%-80% for 10% exposure prevalence), particularly if specificity was low (<97%). PS stratification produced the least biased effect estimates. We observed that the impact of sensitivity and specificity on the bias and coverage for each adjustment method is strongly related to prevalence of exposure: as exposure prevalence decreases and/or outcomes are continuous rather than categorical, the effect of misclassification is magnified, producing larger biases and loss of coverage of 95% confidence intervals. PS matching resulted in unpredictably biased effect estimates.
conclusionsThe results of this study underline the importance of assessing exposure misclassification in observational studies in the context of PS methods. Although PS methods reduce confounding bias, bias owing to nondifferential misclassification is of potentially greater concern.
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